Objective To explore the relationship between changes in brain structural network and the development of post-stroke cognitive impairment(PSCI)in patients after a stroke incident.Methods Prospective collection of data from 209 patients with acute ischemic stroke admitted to Jiangsu University Affiliated Hospital from June 2020 to May 2022.A healthy control group(HC)consisting of 50 individuals without a history of cognitive impairment was also collected during the same period.All participants underwent systematic magnetic resonance imaging(MRI)scans and relevant scale assess-ments,followed by a 12-month longitudinal follow-up.According to the presence of cognitive impairment during follow-up,patients were divided into the post-stroke cognitive impairment group(PSCI)and the post-stroke normal cognitive group(PSNCI).Analysis of variance was used to investigate differences in brain structural network attributes between the groups.Logistic regression models were constructed to investigate the predictive efficacy of brain structural network attributes for PS-CI.Pearson correlation analysis was used to explore the correlations between brain structural network attributes and Montreal Cognitive Assessment(MoCA)scores.Results Analysis of variance results showed significant differences in feature path length(F=3.47,P=0.033),normalized clustering coefficient(F=3.60,P=0.028),normalized feature path length(F=9.47,P＜0.001),global efficiency(F=9.41,P＜0.001),Left middle frontal gyrus node efficiency(F=6.01,P=0.002),right hippocampal node efficiency(F=8.24,P＜0.001),and Right orbital superior frontal gyrus node efficiency(F=4.31,P=0.015)among the three groups.The logistic regression model demonstrated that baseline normalized feature path length(OR=1.87,95％CI 1.84-1.93,P＜0.001)and right hippocampal node efficiency(OR=0.71,95％CI 0.67-0.79,P＜0.001)had good predictive efficacy for PSCI,with area under the receiver operating characteristic curve(AUC)of 0.72 and 0.73,respectively.The combined index had a better predictive efficacy with an AUC of 0.82.The cor-relation analysis results showed that the normalized feature path length(r=-0.61,P=0.002)and right hippocampal node efficiency(r=0.59,P=0.006)of the PSCI group were significantly correlated with the MoCA score.Conclusion Stroke patients with changes in normalized feature path length and right hippocampal node efficiency have a higher risk of cognitive impairment.
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